| 光伏驱动基质控温系统对温室番茄根区的降温效果 |
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| 引用本文： | 张勇,倪欣宇,张柯新,许英杰.光伏驱动基质控温系统对温室番茄根区的降温效果[J].农业工程学报,2020,36(5):212-219. |
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| 作者姓名： | 张勇 倪欣宇 张柯新 许英杰 |
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| 作者单位： | 西北农林科技大学园艺学院,农业农村部西北设施园艺工程重点试验室,杨凌 712100;西北农林科技大学园艺学院,农业农村部西北设施园艺工程重点试验室,杨凌 712100;西北农林科技大学园艺学院,农业农村部西北设施园艺工程重点试验室,杨凌 712100;西北农林科技大学园艺学院,农业农村部西北设施园艺工程重点试验室,杨凌 712100 |
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| 基金项目： | 陕西省重点研发计划项目（2018TSCXL-NY-05-05）；宁夏回族自治区重点研发计划重大项目（2016BZ0901）；节能日光温室结构优化与配套技术开发研究（2017ZDXM-NY-057）；设施农业采光蓄热技术提升研究与示范（2016KTCL02-02） |
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| 摘 要： | 在温室中经常出现短期或持续的高温工况,通常温室内温度环境调控的方法为整体降温,该方法通常会出现无法达到有效降温或高能耗的问题。为解决上述问题,更好地实现温室的周年生产,该研究提出了一种以光伏作为能量来源,以无机相变材料作为储能工质,结合生态智能的环境控制策略,对番茄根区应对高温工况,实现安全连续生产进行了试验研究。结果表明,在温度较高的夏季晴天需2次各约1 h的降温,阴、雨天各仅需1次约1 h降温,其余时段充分利用系统的保冷作用即可达到维持作物舒适生长环境的要求。在试验工况下,典型晴天(2018年7月18日)、阴天(2018年6月30日)、雨天(2018年7月1日)与对照组温度变化相比,该系统实际将试验组基质的平均温度分别降低了8.65、11.38、11.47℃,使番茄根区温度在日间始终低于最高耐受温度(33℃),夜间温度控制在发育的最适温度(22℃)左右。试验进行到第17天时对照组植株全部死亡,试验组保持良好生长状况。该研究所提出的温室控温方法中,保温种植槽单位面积的制冷功率为510.42 W/m^2,基质平均温度降低9.03℃,实现了温室能耗的大幅度降低,而且能够长时间维持降温的效果。使用生态智能种植基质控温的方法和系统,可以实现在超低能耗条件下,解决温室番茄的抗高温安全生产问题。
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| 关 键 词： | 光伏 温室 生态智能 根温 相变材料 夏季 |
| 收稿时间： | 2019/7/16 0:00:00 |
| 修稿时间： | 2019/2/11 0:00:00 |
Cooling performance for tomato root zone with intelligent ecological planting matrix temperature control system driven by photovoltaic in greenhouse |
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| Zhang Yong,Ni Xinyu,Zhang Kexin and Xu Yingjie.Cooling performance for tomato root zone with intelligent ecological planting matrix temperature control system driven by photovoltaic in greenhouse[J].Transactions of the Chinese Society of Agricultural Engineering,2020,36(5):212-219. |
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| Authors: | Zhang Yong Ni Xinyu Zhang Kexin and Xu Yingjie |
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| Institution: | College of Horticulture, Northwest A&F University, Key Laboratory of Protected Horticultural Engineering in Northwest of Ministry of Agriculture and Rural Affairs, Yangling 712100, China,College of Horticulture, Northwest A&F University, Key Laboratory of Protected Horticultural Engineering in Northwest of Ministry of Agriculture and Rural Affairs, Yangling 712100, China,College of Horticulture, Northwest A&F University, Key Laboratory of Protected Horticultural Engineering in Northwest of Ministry of Agriculture and Rural Affairs, Yangling 712100, China and College of Horticulture, Northwest A&F University, Key Laboratory of Protected Horticultural Engineering in Northwest of Ministry of Agriculture and Rural Affairs, Yangling 712100, China |
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| Abstract: | Short-term or continuous high-temperature conditions usually occur during summer greenhouse production. However, the existing cooling measures either fail to achieve effective cooling effects or consume excessive energy. In order to better realize the annual output of the greenhouse, this study used an ecological intelligent planting matrix temperature control system to cool more efficiently in the summer. The system combined control strategies with ecological intelligence to study the safe production of tomato under high temperature conditions. It was driven by photovoltaics, and the excess power was stored in the battery to maintain the system’s operation under adverse weather. The system controlled the temperature of the plant root zone not over 33℃during the day and around 22℃at night. When the system needed to cool down, the DC water pump in the water tank was turned on to drive the water to cool the root zone of the plant through the pipes in the thermal planting groove of the experimental group, and at the same time, the heat exchange with the phase change material was realized by the heat exchanger in the water tank. The matrix temperature at different depths of the substrate in experimental group and control group was compared to evaluate cooling performance of the system. The results showed that it was necessary to cool down twice to reach the appropriate temperature, and it took one hour each time on sunny day in the summer. It took only one time to cool down on cloudy or rainy day. Compared with the control group under the experimental conditions, the average matrix temperatures of experimental group were reduced by 8.65, 11.38, 11.47 ℃ respectively on sunny(2018-07-18), cloudy(2018-06-30) and rainy(2018-07-01) days. The data of the average temperature of the three weathers were calculated by taking the data of sunny, cloudy and rainy days for three consecutive days. The average maximum temperatures at the D8 of the experimental group were 31.26, 29.92, and 27.89 ℃, respectively, which were 6.51, 5.76, and 6.0 ℃ l ower than the control group. The root zone temperature of tomato in experimental group was always lower than the highest tolerance temperature(33 ℃) of tomato root during the day, and kept the optimum temperature(20-23 ℃) throughout the night. All tomato plants in the control group died on the 17 th day of the experiment, while plants in the experimental group still grew well and after that they even blossomed and bore fruit. Under this test condition, it took 4.41×10^6 J energy to run the system at a time, and the cooling power per unit area of the thermal planting groove was 510.42 W/m^2, as the average matrix temperature was reduced by 9.03 ℃. It was far less than the energy consumption required for cooling the entire greenhouse air, and it could meet the high demand for precise temperature control of greenhouses in humid and high-temperature environments. In conclusion, in the case of ultra-low energy consumption, the temperature control method of the ecological intelligent planting matrix temperature control system could be used to solve the problems of high temperature tolerance and safe production of greenhouse tomato planting. |
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| Keywords: | photovoltaic (PV) greenhouse ecological intelligence root temperature phase change materials (PCM) summer |
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